Modeling a logistics hub using the digital footprint method : the implication for open innovation engineering
Optimizing the cargo flows through the nodes of a digital transport corridor is a crucial problem; solving it allows to introduce modern management methods in logistics. This study examines the optimization of the technology of a distribution center as the base node of a third-party logistics networ...
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Gespeichert in:
| Autor*in: |
Shmatko, Alexey [verfasserIn] Barykin, Sergej [verfasserIn] Sergeev, Sergey [verfasserIn] Thirakulwanich, Anuphat [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Rechteinformationen: |
Open Access Namensnennung 4.0 International ; CC BY 4.0 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of open innovation - Basel : MDPI, 2015, 7(2021), 1/59 vom: März, Seite 1-16 |
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| Übergeordnetes Werk: |
volume:7 ; year:2021 ; number:1/59 ; month:03 ; pages:1-16 |
| Links: |
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| DOI / URN: |
10.3390/joitmc7010059 |
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| Katalog-ID: |
1748195646 |
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| 520 | |a Optimizing the cargo flows through the nodes of a digital transport corridor is a crucial problem; solving it allows to introduce modern management methods in logistics. This study examines the optimization of the technology of a distribution center as the base node of a third-party logistics network operator. Our objective consisted in theoretically substantiating the application of mathematical formalisms to describing the passage of stochastic goods flows of a complex structure through a node of a logistics network. To solve the problem, we constructed a mathematical model intended as a decision-making block in the Warehouse Management System software. This paper presents the results of calculations carried out using a computer according to the proposed algorithm. Preliminary results allow to conclude that there is a significant resource for reducing construction and maintenance costs of the distribution center. Quantitatively, the savings will range from 10% to 40%, depending on the terms of delivery of goods and the degree of market uncertainty. An example of a practical calculation using the developed mathematical model is given. The calculations were performed for Huawei, a key global provider of ICT infrastructure and smart terminals. The algorithms were designed to account for uncertainty, which allows to use the results for risk management applications. In practice, this theoretical concept can serve as a basis for digital logistics platforms, increasing the speed of delivery of goods and cargo and the profitability of logistics as a result. The solution to this problem will allow to consider the nodes of logistics networks as smart independent divisions with an information interface for interaction built into a digital logistics platform. The role of these nodes is to make the best decisions in handling cargo flows. As the next stage of research, we plan to develop algorithms for coordinating the information flows reflecting transport activities and forming the material flows entering and leaving the distribution centers. | ||
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10.3390/joitmc7010059 doi 10419/241644 hdl (DE-627)1748195646 (DE-599)KXP1748195646 DE-627 ger DE-627 rda eng Shmatko, Alexey verfasserin aut Modeling a logistics hub using the digital footprint method the implication for open innovation engineering Alexey Shmatko, Sergey Barykin, Sergey Sergeev and Anuphat Thirakulwanich 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Optimizing the cargo flows through the nodes of a digital transport corridor is a crucial problem; solving it allows to introduce modern management methods in logistics. This study examines the optimization of the technology of a distribution center as the base node of a third-party logistics network operator. Our objective consisted in theoretically substantiating the application of mathematical formalisms to describing the passage of stochastic goods flows of a complex structure through a node of a logistics network. To solve the problem, we constructed a mathematical model intended as a decision-making block in the Warehouse Management System software. This paper presents the results of calculations carried out using a computer according to the proposed algorithm. Preliminary results allow to conclude that there is a significant resource for reducing construction and maintenance costs of the distribution center. Quantitatively, the savings will range from 10% to 40%, depending on the terms of delivery of goods and the degree of market uncertainty. An example of a practical calculation using the developed mathematical model is given. The calculations were performed for Huawei, a key global provider of ICT infrastructure and smart terminals. The algorithms were designed to account for uncertainty, which allows to use the results for risk management applications. In practice, this theoretical concept can serve as a basis for digital logistics platforms, increasing the speed of delivery of goods and cargo and the profitability of logistics as a result. The solution to this problem will allow to consider the nodes of logistics networks as smart independent divisions with an information interface for interaction built into a digital logistics platform. The role of these nodes is to make the best decisions in handling cargo flows. As the next stage of research, we plan to develop algorithms for coordinating the information flows reflecting transport activities and forming the material flows entering and leaving the distribution centers. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ digital logistics (dpeaa)DE-206 digital supply chains (dpeaa)DE-206 Huawei (dpeaa)DE-206 production management (dpeaa)DE-206 Barykin, Sergej verfasserin (DE-588)1305766555 (DE-627)1862626715 aut Sergeev, Sergey verfasserin aut Thirakulwanich, Anuphat verfasserin aut Enthalten in Journal of open innovation Basel : MDPI, 2015 7(2021), 1/59 vom: März, Seite 1-16 Online-Ressource (DE-627)833526413 (DE-600)2832108-X (DE-576)444393463 2199-8531 nnns volume:7 year:2021 number:1/59 month:03 pages:1-16 https://www.mdpi.com/2199-8531/7/1/59/pdf Verlag kostenfrei https://doi.org/10.3390/joitmc7010059 Resolving-System kostenfrei http://hdl.handle.net/10419/241644 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 7 2021 1/59 3 1-16 26 01 0206 3851667093 x1z 12-02-21 2403 01 DE-LFER 3882894407 00 --%%-- --%%-- n --%%-- l01 08-03-21 2403 01 DE-LFER https://doi.org/10.3390/joitmc7010059 2403 01 DE-LFER https://www.mdpi.com/2199-8531/7/1/59/pdf |
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10.3390/joitmc7010059 doi 10419/241644 hdl (DE-627)1748195646 (DE-599)KXP1748195646 DE-627 ger DE-627 rda eng Shmatko, Alexey verfasserin aut Modeling a logistics hub using the digital footprint method the implication for open innovation engineering Alexey Shmatko, Sergey Barykin, Sergey Sergeev and Anuphat Thirakulwanich 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Optimizing the cargo flows through the nodes of a digital transport corridor is a crucial problem; solving it allows to introduce modern management methods in logistics. This study examines the optimization of the technology of a distribution center as the base node of a third-party logistics network operator. Our objective consisted in theoretically substantiating the application of mathematical formalisms to describing the passage of stochastic goods flows of a complex structure through a node of a logistics network. To solve the problem, we constructed a mathematical model intended as a decision-making block in the Warehouse Management System software. This paper presents the results of calculations carried out using a computer according to the proposed algorithm. Preliminary results allow to conclude that there is a significant resource for reducing construction and maintenance costs of the distribution center. Quantitatively, the savings will range from 10% to 40%, depending on the terms of delivery of goods and the degree of market uncertainty. An example of a practical calculation using the developed mathematical model is given. The calculations were performed for Huawei, a key global provider of ICT infrastructure and smart terminals. The algorithms were designed to account for uncertainty, which allows to use the results for risk management applications. In practice, this theoretical concept can serve as a basis for digital logistics platforms, increasing the speed of delivery of goods and cargo and the profitability of logistics as a result. The solution to this problem will allow to consider the nodes of logistics networks as smart independent divisions with an information interface for interaction built into a digital logistics platform. The role of these nodes is to make the best decisions in handling cargo flows. As the next stage of research, we plan to develop algorithms for coordinating the information flows reflecting transport activities and forming the material flows entering and leaving the distribution centers. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ digital logistics (dpeaa)DE-206 digital supply chains (dpeaa)DE-206 Huawei (dpeaa)DE-206 production management (dpeaa)DE-206 Barykin, Sergej verfasserin (DE-588)1305766555 (DE-627)1862626715 aut Sergeev, Sergey verfasserin aut Thirakulwanich, Anuphat verfasserin aut Enthalten in Journal of open innovation Basel : MDPI, 2015 7(2021), 1/59 vom: März, Seite 1-16 Online-Ressource (DE-627)833526413 (DE-600)2832108-X (DE-576)444393463 2199-8531 nnns volume:7 year:2021 number:1/59 month:03 pages:1-16 https://www.mdpi.com/2199-8531/7/1/59/pdf Verlag kostenfrei https://doi.org/10.3390/joitmc7010059 Resolving-System kostenfrei http://hdl.handle.net/10419/241644 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 7 2021 1/59 3 1-16 26 01 0206 3851667093 x1z 12-02-21 2403 01 DE-LFER 3882894407 00 --%%-- --%%-- n --%%-- l01 08-03-21 2403 01 DE-LFER https://doi.org/10.3390/joitmc7010059 2403 01 DE-LFER https://www.mdpi.com/2199-8531/7/1/59/pdf |
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10.3390/joitmc7010059 doi 10419/241644 hdl (DE-627)1748195646 (DE-599)KXP1748195646 DE-627 ger DE-627 rda eng Shmatko, Alexey verfasserin aut Modeling a logistics hub using the digital footprint method the implication for open innovation engineering Alexey Shmatko, Sergey Barykin, Sergey Sergeev and Anuphat Thirakulwanich 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Optimizing the cargo flows through the nodes of a digital transport corridor is a crucial problem; solving it allows to introduce modern management methods in logistics. This study examines the optimization of the technology of a distribution center as the base node of a third-party logistics network operator. Our objective consisted in theoretically substantiating the application of mathematical formalisms to describing the passage of stochastic goods flows of a complex structure through a node of a logistics network. To solve the problem, we constructed a mathematical model intended as a decision-making block in the Warehouse Management System software. This paper presents the results of calculations carried out using a computer according to the proposed algorithm. Preliminary results allow to conclude that there is a significant resource for reducing construction and maintenance costs of the distribution center. Quantitatively, the savings will range from 10% to 40%, depending on the terms of delivery of goods and the degree of market uncertainty. An example of a practical calculation using the developed mathematical model is given. The calculations were performed for Huawei, a key global provider of ICT infrastructure and smart terminals. The algorithms were designed to account for uncertainty, which allows to use the results for risk management applications. In practice, this theoretical concept can serve as a basis for digital logistics platforms, increasing the speed of delivery of goods and cargo and the profitability of logistics as a result. The solution to this problem will allow to consider the nodes of logistics networks as smart independent divisions with an information interface for interaction built into a digital logistics platform. The role of these nodes is to make the best decisions in handling cargo flows. As the next stage of research, we plan to develop algorithms for coordinating the information flows reflecting transport activities and forming the material flows entering and leaving the distribution centers. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ digital logistics (dpeaa)DE-206 digital supply chains (dpeaa)DE-206 Huawei (dpeaa)DE-206 production management (dpeaa)DE-206 Barykin, Sergej verfasserin (DE-588)1305766555 (DE-627)1862626715 aut Sergeev, Sergey verfasserin aut Thirakulwanich, Anuphat verfasserin aut Enthalten in Journal of open innovation Basel : MDPI, 2015 7(2021), 1/59 vom: März, Seite 1-16 Online-Ressource (DE-627)833526413 (DE-600)2832108-X (DE-576)444393463 2199-8531 nnns volume:7 year:2021 number:1/59 month:03 pages:1-16 https://www.mdpi.com/2199-8531/7/1/59/pdf Verlag kostenfrei https://doi.org/10.3390/joitmc7010059 Resolving-System kostenfrei http://hdl.handle.net/10419/241644 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 7 2021 1/59 3 1-16 26 01 0206 3851667093 x1z 12-02-21 2403 01 DE-LFER 3882894407 00 --%%-- --%%-- n --%%-- l01 08-03-21 2403 01 DE-LFER https://doi.org/10.3390/joitmc7010059 2403 01 DE-LFER https://www.mdpi.com/2199-8531/7/1/59/pdf |
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10.3390/joitmc7010059 doi 10419/241644 hdl (DE-627)1748195646 (DE-599)KXP1748195646 DE-627 ger DE-627 rda eng Shmatko, Alexey verfasserin aut Modeling a logistics hub using the digital footprint method the implication for open innovation engineering Alexey Shmatko, Sergey Barykin, Sergey Sergeev and Anuphat Thirakulwanich 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Optimizing the cargo flows through the nodes of a digital transport corridor is a crucial problem; solving it allows to introduce modern management methods in logistics. This study examines the optimization of the technology of a distribution center as the base node of a third-party logistics network operator. Our objective consisted in theoretically substantiating the application of mathematical formalisms to describing the passage of stochastic goods flows of a complex structure through a node of a logistics network. To solve the problem, we constructed a mathematical model intended as a decision-making block in the Warehouse Management System software. This paper presents the results of calculations carried out using a computer according to the proposed algorithm. Preliminary results allow to conclude that there is a significant resource for reducing construction and maintenance costs of the distribution center. Quantitatively, the savings will range from 10% to 40%, depending on the terms of delivery of goods and the degree of market uncertainty. An example of a practical calculation using the developed mathematical model is given. The calculations were performed for Huawei, a key global provider of ICT infrastructure and smart terminals. The algorithms were designed to account for uncertainty, which allows to use the results for risk management applications. In practice, this theoretical concept can serve as a basis for digital logistics platforms, increasing the speed of delivery of goods and cargo and the profitability of logistics as a result. The solution to this problem will allow to consider the nodes of logistics networks as smart independent divisions with an information interface for interaction built into a digital logistics platform. The role of these nodes is to make the best decisions in handling cargo flows. As the next stage of research, we plan to develop algorithms for coordinating the information flows reflecting transport activities and forming the material flows entering and leaving the distribution centers. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ digital logistics (dpeaa)DE-206 digital supply chains (dpeaa)DE-206 Huawei (dpeaa)DE-206 production management (dpeaa)DE-206 Barykin, Sergej verfasserin (DE-588)1305766555 (DE-627)1862626715 aut Sergeev, Sergey verfasserin aut Thirakulwanich, Anuphat verfasserin aut Enthalten in Journal of open innovation Basel : MDPI, 2015 7(2021), 1/59 vom: März, Seite 1-16 Online-Ressource (DE-627)833526413 (DE-600)2832108-X (DE-576)444393463 2199-8531 nnns volume:7 year:2021 number:1/59 month:03 pages:1-16 https://www.mdpi.com/2199-8531/7/1/59/pdf Verlag kostenfrei https://doi.org/10.3390/joitmc7010059 Resolving-System kostenfrei http://hdl.handle.net/10419/241644 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 7 2021 1/59 3 1-16 26 01 0206 3851667093 x1z 12-02-21 2403 01 DE-LFER 3882894407 00 --%%-- --%%-- n --%%-- l01 08-03-21 2403 01 DE-LFER https://doi.org/10.3390/joitmc7010059 2403 01 DE-LFER https://www.mdpi.com/2199-8531/7/1/59/pdf |
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10.3390/joitmc7010059 doi 10419/241644 hdl (DE-627)1748195646 (DE-599)KXP1748195646 DE-627 ger DE-627 rda eng Shmatko, Alexey verfasserin aut Modeling a logistics hub using the digital footprint method the implication for open innovation engineering Alexey Shmatko, Sergey Barykin, Sergey Sergeev and Anuphat Thirakulwanich 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Optimizing the cargo flows through the nodes of a digital transport corridor is a crucial problem; solving it allows to introduce modern management methods in logistics. This study examines the optimization of the technology of a distribution center as the base node of a third-party logistics network operator. Our objective consisted in theoretically substantiating the application of mathematical formalisms to describing the passage of stochastic goods flows of a complex structure through a node of a logistics network. To solve the problem, we constructed a mathematical model intended as a decision-making block in the Warehouse Management System software. This paper presents the results of calculations carried out using a computer according to the proposed algorithm. Preliminary results allow to conclude that there is a significant resource for reducing construction and maintenance costs of the distribution center. Quantitatively, the savings will range from 10% to 40%, depending on the terms of delivery of goods and the degree of market uncertainty. An example of a practical calculation using the developed mathematical model is given. The calculations were performed for Huawei, a key global provider of ICT infrastructure and smart terminals. The algorithms were designed to account for uncertainty, which allows to use the results for risk management applications. In practice, this theoretical concept can serve as a basis for digital logistics platforms, increasing the speed of delivery of goods and cargo and the profitability of logistics as a result. The solution to this problem will allow to consider the nodes of logistics networks as smart independent divisions with an information interface for interaction built into a digital logistics platform. The role of these nodes is to make the best decisions in handling cargo flows. As the next stage of research, we plan to develop algorithms for coordinating the information flows reflecting transport activities and forming the material flows entering and leaving the distribution centers. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ digital logistics (dpeaa)DE-206 digital supply chains (dpeaa)DE-206 Huawei (dpeaa)DE-206 production management (dpeaa)DE-206 Barykin, Sergej verfasserin (DE-588)1305766555 (DE-627)1862626715 aut Sergeev, Sergey verfasserin aut Thirakulwanich, Anuphat verfasserin aut Enthalten in Journal of open innovation Basel : MDPI, 2015 7(2021), 1/59 vom: März, Seite 1-16 Online-Ressource (DE-627)833526413 (DE-600)2832108-X (DE-576)444393463 2199-8531 nnns volume:7 year:2021 number:1/59 month:03 pages:1-16 https://www.mdpi.com/2199-8531/7/1/59/pdf Verlag kostenfrei https://doi.org/10.3390/joitmc7010059 Resolving-System kostenfrei http://hdl.handle.net/10419/241644 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 7 2021 1/59 3 1-16 26 01 0206 3851667093 x1z 12-02-21 2403 01 DE-LFER 3882894407 00 --%%-- --%%-- n --%%-- l01 08-03-21 2403 01 DE-LFER https://doi.org/10.3390/joitmc7010059 2403 01 DE-LFER https://www.mdpi.com/2199-8531/7/1/59/pdf |
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Modeling a logistics hub using the digital footprint method the implication for open innovation engineering |
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Optimizing the cargo flows through the nodes of a digital transport corridor is a crucial problem; solving it allows to introduce modern management methods in logistics. This study examines the optimization of the technology of a distribution center as the base node of a third-party logistics network operator. Our objective consisted in theoretically substantiating the application of mathematical formalisms to describing the passage of stochastic goods flows of a complex structure through a node of a logistics network. To solve the problem, we constructed a mathematical model intended as a decision-making block in the Warehouse Management System software. This paper presents the results of calculations carried out using a computer according to the proposed algorithm. Preliminary results allow to conclude that there is a significant resource for reducing construction and maintenance costs of the distribution center. Quantitatively, the savings will range from 10% to 40%, depending on the terms of delivery of goods and the degree of market uncertainty. An example of a practical calculation using the developed mathematical model is given. The calculations were performed for Huawei, a key global provider of ICT infrastructure and smart terminals. The algorithms were designed to account for uncertainty, which allows to use the results for risk management applications. In practice, this theoretical concept can serve as a basis for digital logistics platforms, increasing the speed of delivery of goods and cargo and the profitability of logistics as a result. The solution to this problem will allow to consider the nodes of logistics networks as smart independent divisions with an information interface for interaction built into a digital logistics platform. The role of these nodes is to make the best decisions in handling cargo flows. As the next stage of research, we plan to develop algorithms for coordinating the information flows reflecting transport activities and forming the material flows entering and leaving the distribution centers. |
| abstractGer |
Optimizing the cargo flows through the nodes of a digital transport corridor is a crucial problem; solving it allows to introduce modern management methods in logistics. This study examines the optimization of the technology of a distribution center as the base node of a third-party logistics network operator. Our objective consisted in theoretically substantiating the application of mathematical formalisms to describing the passage of stochastic goods flows of a complex structure through a node of a logistics network. To solve the problem, we constructed a mathematical model intended as a decision-making block in the Warehouse Management System software. This paper presents the results of calculations carried out using a computer according to the proposed algorithm. Preliminary results allow to conclude that there is a significant resource for reducing construction and maintenance costs of the distribution center. Quantitatively, the savings will range from 10% to 40%, depending on the terms of delivery of goods and the degree of market uncertainty. An example of a practical calculation using the developed mathematical model is given. The calculations were performed for Huawei, a key global provider of ICT infrastructure and smart terminals. The algorithms were designed to account for uncertainty, which allows to use the results for risk management applications. In practice, this theoretical concept can serve as a basis for digital logistics platforms, increasing the speed of delivery of goods and cargo and the profitability of logistics as a result. The solution to this problem will allow to consider the nodes of logistics networks as smart independent divisions with an information interface for interaction built into a digital logistics platform. The role of these nodes is to make the best decisions in handling cargo flows. As the next stage of research, we plan to develop algorithms for coordinating the information flows reflecting transport activities and forming the material flows entering and leaving the distribution centers. |
| abstract_unstemmed |
Optimizing the cargo flows through the nodes of a digital transport corridor is a crucial problem; solving it allows to introduce modern management methods in logistics. This study examines the optimization of the technology of a distribution center as the base node of a third-party logistics network operator. Our objective consisted in theoretically substantiating the application of mathematical formalisms to describing the passage of stochastic goods flows of a complex structure through a node of a logistics network. To solve the problem, we constructed a mathematical model intended as a decision-making block in the Warehouse Management System software. This paper presents the results of calculations carried out using a computer according to the proposed algorithm. Preliminary results allow to conclude that there is a significant resource for reducing construction and maintenance costs of the distribution center. Quantitatively, the savings will range from 10% to 40%, depending on the terms of delivery of goods and the degree of market uncertainty. An example of a practical calculation using the developed mathematical model is given. The calculations were performed for Huawei, a key global provider of ICT infrastructure and smart terminals. The algorithms were designed to account for uncertainty, which allows to use the results for risk management applications. In practice, this theoretical concept can serve as a basis for digital logistics platforms, increasing the speed of delivery of goods and cargo and the profitability of logistics as a result. The solution to this problem will allow to consider the nodes of logistics networks as smart independent divisions with an information interface for interaction built into a digital logistics platform. The role of these nodes is to make the best decisions in handling cargo flows. As the next stage of research, we plan to develop algorithms for coordinating the information flows reflecting transport activities and forming the material flows entering and leaving the distribution centers. |
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| container_issue |
1/59 |
| title_short |
Modeling a logistics hub using the digital footprint method |
| url |
https://www.mdpi.com/2199-8531/7/1/59/pdf https://doi.org/10.3390/joitmc7010059 http://hdl.handle.net/10419/241644 |
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Barykin, Sergej Sergeev, Sergey Thirakulwanich, Anuphat |
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Barykin, Sergey Evgenievich Barykin, Sergey Barykin, Sergei Barykin, Sergey Yevgenievich Barkyn, Sergey Evgenevich Barykin, Sergej E. Barykin, Sergej Evgenʹevič Barykin, Sergej |
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Barykin, Sergey Evgenievich Barykin, Sergey Barykin, Sergei Barykin, Sergey Yevgenievich Barkyn, Sergey Evgenevich Barykin, Sergej E. Barykin, Sergej Evgenʹevič Barykin, Sergej |
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| score |
7.400571 |